The present paper deals with an original multi–objective optimization approach to the mitigation of the acoustic impact of commercial aircraft. The method is based on the coupling of the classical noise level reduction approach and an innovative sound-quality assessment method, developed during the EC–funded projects SEFA (Sound Engineering For Aircraft, FP6, 2004–2007) and COSMA (Community Noise Solutions to Minimise aircraft noise Annoyance, FP7, 2009–2012). Indeed, the increase of air traffic and the rapid expansion of urban areas around airports are making the aviation community noise a key aspect of the sustainable development of the transportation system. As a consequence, the scientific and industrial research community is focusing the attention on the development of innovative aircraft configurations, aimed at a substantial reduction of the acoustic impact of aircraft. Unfortunately, such a new concepts will be ready for operation only in the long–term, thus making extremely urgent the identification of alternative strategies to mitigate the impact on the residential community. The present work addresses the problem by integrating into the multi–objective, multi-disciplinary optimization framework developed and validated in COSMA, the sound–matching criterion developed within SEFA, with a noise–level based indicator minimization. Specifically, the two merit factors to be minimized are the norm of the difference between the noise produced by the configuration under analysis and a target sound, and the EPNL (effective perceived noise level) at a certification point. The target sounds are obtained by synthesis, using sound engineering techniques aimed at the sound quality improvement, on the basis of the results of the psychometric tests campaigns performed in SEFA and COSMA. The simultaneous reduction of the two objective functions is achieved through a multi-objective optimization problem adopting global evolution methods, as implemented within the MDO environment FRIDA (FRamework for Innovative Design in Aeronautics). Results will be presented for procedure optimization in terms of Pareto fronts, for two types of aircraft in both take off and landing conditions.
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